Cite as:
G&ouml;ttlicher, D.; Obreg&oacute;n, A.; Homeier, J.; Rollenbeck, R.; Nauss, T. &amp; Bendix, J. (2009): <b>Land-cover classification in the Andes of southern Ecuador using Landsat ETM+ data as a basis for SVAT modelling</b>. <i>International Journal of Remote Sensing</i> <b>30</b>, 1867-1886.

Resource Description

Title: Land-cover classification in the Andes of southern Ecuador using Landsat ETM+ data as a basis for SVAT modelling
Short Name: Land-cover classification in southern Ecuador
FOR816dw ID: 449
Publication Date: 2009-04-01
License and Usage Rights:
Resource Owner(s):
Individual: Dietrich Göttlicher
Individual: André Obregón
Individual: Jürgen Homeier
Individual: Ruetger Rollenbeck
Individual: Thomas Nauss
Individual: Jörg Bendix
A land-cover classification is needed to deduce surface boundary conditions for a<br/> soil?vegetation?atmosphere transfer (SVAT) scheme that is operated by a<br/> geoecological research unit working in the Andes of southern Ecuador. Landsat<br/> Enhanced Thematic Mapper Plus (ETM + ) data are used to classify distinct<br/> vegetation types in the tropical mountain forest. Besides a hard classification, a<br/> soft classification technique is applied. Dempster?Shafer evidence theory is used<br/> to analyse the quality of the spectral training sites and a modified linear spectral<br/> unmixing technique is selected to produce abundancies of the spectral<br/> endmembers. The hard classification provides very good results, with a Kappa<br/> value of 0.86. The Dempster?Shafer ambiguity underlines the good quality of the<br/> training sites and the probability guided spectral unmixing is chosen for the<br/> determination of plant functional types for the land model. A similar model run<br/> with a spatial distribution of land cover from both the hard and the soft<br/> classification processes clearly points to more realistic model results by using the<br/> land surface based on the probability guided spectral unmixing technique.
Literature type specific fields:
Journal: International Journal of Remote Sensing
Volume: 30
Page Range: 1867-1886
Publisher: Taylor & Francis
Metadata Provider:
Individual: Dietrich Göttlicher
Online Distribution:
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